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. Author manuscript; available in PMC: 2020 Oct 1.
Published in final edited form as: Magn Reson Med. 2019 May 2;82(4):1452–1461. doi: 10.1002/mrm.27771

Figure 2. Convolutional neural network for motion artifact detection.

Figure 2.

A motion corrupted image is input as two channels (corresponding to the real and imaginary components) to a 27-layer patch-based CNN consisting of convolutional layers, batch normalization, and ReLU nonlinearities. The network outputs the image artifacts, which can be subtracted from the input image to arrive at a motion mitigated image.